A challenge faced by a consumer when buying a car, especially a used car, is that there is no intuitive and economical way to determine whether a car is mechanically reliable, involves any accident, or has any hidden issue that is not readily appreciable by an average person. A car buyer may purchase a vehicle history report to examine the history of a car. However, such a report is typically not free of charge and the cost may add up when multiple reports are needed. In addition, even if a buyer manages to obtain a vehicle history report, information on the report may be difficult to understand. For example, such a report may be text-based and lack visual indications as to, for instance, the extent and severity of past accident(s). Moreover, to obtain the report, the buyer may be required to input the vehicle identification number (VIN), which is not always readily available.
Thus, there is a need for systems and methods capable of streamlining the car buying process by automatically obtaining vehicle information based on a picture of the vehicle, analyzing the vehicle information to extract vehicle history data, and presenting the vehicle history data in augmented reality to assist a buyer to make purchase decisions.